CS 4150 — Game Artificial Intelligence
4 semester hoursUndergraduateLectureNUpath CENUpath WIusually offered: springtypical days: WBostonTraditional
Offers an overview of classical and modern approaches to artificial intelligence in digital games. Focuses on the creation of believable agents and environments with the goal of providing a fun and engaging experience to a player. Covers player modeling, procedural content generation, behavior trees, interactive narrative, decision-making systems, cognitive modeling, and path planning. Explores different approaches for behavior generation, including learning and rule-based systems. Requires students to complete several individual assignments in these areas to apply the concepts covered in class. Students choose a group final project to explore one aspect of artificial intelligence for games in further depth. Offers students an opportunity to learn team management and communication. Students who do not meet course prerequisites may seek permission of instructor.
Prerequisites
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Spring 2024 | 1 | 30 | 30 | 100% | 0.0 |
| Spring 2025 | 1 | 34 | 37 | 92% | 3.0 |
| Spring 2026 | 1 | 34 | 40 | 85% | 6.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 0% · W 69% · Th 31% · F 0%
Common patterns: W (69% of sections), R (31% of sections) — in patterns, R means Thursday
Professors
Spring
- Damian Isla (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (CS course descriptions) · Student reviews on RateMyHusky · All CS courses · Plan it at numap.app